Attitude May Be Everything, But Is Everything an Attitude? Cognitive Distortions May Not Be Evaluations of Rape
Bibliographic record
Abstract
Cognitive distortions are often referred to as attitudes toward rape in theory, research, and clinical practice pertaining to sexual aggression. In the social-psychological literature, however, attitudes are typically defined as evaluations; thus, in this context, attitudes toward rape are considered evaluations of rape (e.g., rape is negative vs. positive). The purpose of the current study was to explore whether a widely used measure of cognitive distortions (RAPE Scale; Bumby, 1996) assesses evaluation of rape, and, if not, whether evaluation of rape and the cognitions assessed by the RAPE Scale are independently associated with sexually aggressive behavior. Participants (660 male undergraduate students) completed the RAPE Scale as well as measures of evaluation of rape and sexually aggressive behavior. An exploratory factor analysis revealed that the RAPE Scale items formed a correlated but distinct factor from the Evaluation of Rape Scale items. Regression analyses indicated that the Evaluation of Rape Scale and the RAPE Scale had small to moderate independent associations with self-report measures of sexually aggressive behavior. Our results suggest that evaluation of rape may be distinct from cognitive distortions regarding rape, and both evaluation and cognitive distortions may be relevant for understanding sexual violence.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".